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Looking at birth order in Greg Clark's sample
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# R code for https://open.substack.com/pub/wyclif/p/does-birth-order-matter | |
library(openxlsx) | |
library(tidyverse) | |
library(fixest) | |
library(huxtable) | |
# get the data from the PNAS article | |
vars1 <- openxlsx::read.xlsx("pnas.2300926120.sd01.xlsx", sheet = 1) | |
sd1 <- openxlsx::read.xlsx("pnas.2300926120.sd01.xlsx", sheet = 2) | |
sd1 <- as_tibble(sd1) | |
sd1 <- distinct(sd1, pid, .keep_all = TRUE) # remove 19 dupes | |
sd_sibs <- sd1 |> | |
filter(! is.na(pid_fath), ! is.na(pid_moth)) |> | |
arrange(byr) |> | |
mutate( | |
n_sibs = n(), | |
birth_order = min_rank(byr), | |
first_child = birth_order == 1, | |
.by = c(pid_fath, pid_moth) # within sib-groups with the same parents | |
) |> | |
filter(n_sibs <= 6) | |
sd_sibs <- sd_sibs |> | |
mutate( | |
n_wives_fath = n_distinct(pid_moth), | |
.by = pid_fath | |
) |> | |
filter( | |
n_wives_fath <= 2 # one guy with 1291 wives... | |
) | |
table(`N siblings` = sd_sibs$n_sibs, `Birth order` = sd_sibs$birth_order) |> | |
prop.table(1) |> | |
round(2) | |
mod <- list() | |
# higher education | |
mod$ded <- feols(ded ~ birth_order + byr | pid_fath^pid_moth, data = sd_sibs) | |
# literacy at marriage | |
mod$lit <- feols(lit ~ birth_order + byr | pid_fath^pid_moth, data = sd_sibs) | |
# occupational status | |
mod$occ <- feols(occ ~ birth_order + byr | pid_fath^pid_moth, data = sd_sibs) | |
# log house value | |
mod$lhv <- feols(lhv ~ birth_order + byr | pid_fath^pid_moth, data = sd_sibs) | |
# index of multiple deprivation 2019 | |
mod$imd <- feols(imd ~ birth_order + byr | pid_fath^pid_moth, data = sd_sibs) | |
# table 1 | |
huxreg(mod, | |
statistics = c(N = "nobs", "R2" = "r.squared", "Within R2" = "within.r.squared")) | |
# in the pooled regressions, we need to calculate father's age explicitly | |
sd1$pid <- as.character(sd1$pid) | |
sd_sibs <- left_join(sd_sibs, | |
sd1 |> select(pid, byrf = byr), | |
by = c("pid_fath" = "pid")) | |
sd_sibs$fath_age_birth <- sd_sibs$byr - sd_sibs$byrf | |
mod_pool <- list() | |
mod_pool$"Higher ed" <- feols(ded ~ birth_order + fath_age_birth | n_sibs, data = sd_sibs, vcov = cluster ~ pid_fath+pid_moth) | |
mod_pool$"Literacy" <- feols(lit ~ birth_order + fath_age_birth | n_sibs, data = sd_sibs, vcov = cluster ~ pid_fath+pid_moth) | |
mod_pool$"Occ. status" <- feols(occ ~ birth_order + fath_age_birth | n_sibs, data = sd_sibs, vcov = cluster ~ pid_fath+pid_moth) | |
mod_pool$"House value" <- feols(lhv ~ birth_order + fath_age_birth | n_sibs, data = sd_sibs, vcov = cluster ~ pid_fath+pid_moth) | |
mod_pool$"IMD 2019" <- feols(imd ~ birth_order + fath_age_birth | n_sibs, data = sd_sibs, vcov = cluster ~ pid_fath+pid_moth) | |
# table 2 | |
huxreg(mod_pool, statistics = c(N = "nobs", R2 = "r.squared", "Within R2" = "within.r.squared")) | |
# other stuff not in the post | |
# dummy for first child only | |
mod_1st <- list() | |
mod_1st[["ded"]] <- feols(ded ~ first_child + byr | pid_fath^pid_moth, data = sd_sibs) | |
mod_1st[["lit"]] <- feols(lit ~ first_child + byr | pid_fath^pid_moth, data = sd_sibs) | |
mod_1st[["occ"]] <- feols(occ ~ first_child + byr | pid_fath^pid_moth, data = sd_sibs) | |
mod_1st[["lhv"]] <- feols(lhv ~ first_child + byr | pid_fath^pid_moth, data = sd_sibs) | |
mod_1st[["imd"]] <- feols(imd ~ first_child + byr | pid_fath^pid_moth, data = sd_sibs) | |
# without controlling for parental age | |
mod_simple <- list() | |
mod_simple[["ded"]] <- feols(ded ~ birth_order | pid_fath^pid_moth, data = sd_sibs) | |
mod_simple[["lit"]] <- feols(lit ~ birth_order | pid_fath^pid_moth, data = sd_sibs) | |
mod_simple[["occ"]] <- feols(occ ~ birth_order | pid_fath^pid_moth, data = sd_sibs) | |
mod_simple[["lhv"]] <- feols(lhv ~ birth_order | pid_fath^pid_moth, data = sd_sibs) | |
mod_simple[["imd"]] <- feols(imd ~ birth_order | pid_fath^pid_moth, data = sd_sibs) | |
cor(demean(fath_age_birth ~ n_sibs, data = sd_sibs, na.rm = FALSE), | |
demean(birth_order ~ n_sibs, data = sd_sibs, na.rm = FALSE), | |
use = "complete") |
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